A major and resource-intensive step in price calculations in business transactions (e.g., order processing, invoicing) is an inquiry or lookup into a price master database. Depending upon the complexity of the price calculation rules (i.e., pricing schema or pricing procedure), during pricing many database lookups need to be made against price master database tables. These lookups could relate to prices, discounts, surcharges, taxes, etc. Usually, these look-ups take time, and because of that, the end user response time is degraded. In order to avoid this degradation in response time, pricing calculation applications usually cache the price master data in a shared memory of a system. However, caching price master data in shared memory consumes additional memory and increases the total cost of ownership (TCO), especially for large customers. Additionally, in order to manage such a cache (i.e., make sure that it is up-to-date with the price master database image), cache handlers have to employ additional services, which sometimes occupy many system resources (like work processes), and that make the system almost unusable for critical business processes.